Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …

Abstract Machine learning (ML) models can accelerate the development of efficient internal
combustion engines. This study assessed the feasibility of data-driven methods toward …

Predictions made by climate researchers are highly worrisome and demand rapid action to
avoid the threat of climate catastrophe. Global energy systems must be transformed as …

When monitoring combustion conditions, detecting minor variations, which may be complex
even for the human eye, is critical for providing a fast response and correcting deviations …

A combined numerical and experimental investigation is carried out to analyze the cycle-to-
cycle variations (CCV) in an optically accessible spark-ignition engine with port fuel …

Cyclic variability is investigated in an optically accessible single-cylinder spark-ignition
research engine by introducing artificial exhaust gas in controlled amounts to the …

Machine learning (ML) models based on a large data set of in-cylinder flow fields of an IC
engine obtained by high-speed particle image velocimetry allow the identification of relevant …

Understanding, modeling, and reducing the cycle-to-cycle variability (CCV) of combustion in
internal combustion engines (ICE) is a critical challenge to design engines of high efficiency …

In this work, the phenomenon of cycle-to-cycle variability (CCV) of combustion in a spark
ignition engine is investigated to give a deeper understanding of CCV generation. The main …

In this work, the cycle-to-cycle variations (CCV) and their correlations to intake charge
fluctuation of a motorcycle engine under wide operating conditions were investigated by …